Can Zhu

1 month ago | nature.com | Yali Liu |Can Zhu

In order to explore the application of deep learning (DL) and artificial intelligence (AI) technologies in art education, this work proposes and optimizes an innovative art creation system—Creative Intelligence Cloud (CIC). The system combines a deep generative adversarial network and convolutional neural network, aiming to enhance the automation level, consistency of artistic styles, and creation efficiency in art creation. This work first analyzes existing art creation methods. It points out the shortcomings of traditional systems in terms of image quality, style transfer, and computational performance, especially the application limitations in real teaching scenarios. Therefore, this work designs an art creation model optimized by DL and validates and evaluates it through extensive experiments. The experimental results show that CIC outperforms existing mainstream models in multiple dimensions, including image quality, computational performance, user experience, and style creation. For example, in image quality evaluation, CIC achieves high scores in clarity (0.89), detail performance (0.85), style consistency (0.87), and color accuracy (0.91). In terms of computational performance and resource consumption, CIC shows its superiority, with a training time of only 1500 s, memory consumption of 4.9GB, and a Graphics Processing Unit resource usage rate of 70%. Compared to models such as the Visual Perception Generative Adversarial Network and Artistic Recognition and Transfer Style Convolutional Neural Network, CIC is more efficient and consumes fewer resources. Furthermore, CIC’s scores in user experience and style transfer capability are significantly higher than those of other models, providing smoother and more creatively rich art creation tools for art education. Therefore, this work offers new ideas and methods for the application of DL and AI technologies in art creation and art education, and promotes the practical use of AI in art education. The work has certain academic contributions and practical value.

Nov 16, 2024 | pericles.pericles-prod.literatumonline.com | Yiwei Sun |Wei Zhang |Zhiwen Luo |Can Zhu

Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description adfm202415778-sup-0001-SuppMat.docx6.9 MB Supporting Information References 1a) , , , , , , Lancet 2016, 387, 386; b) , , , , , , , , , , , , , , , , , Proc Natl Acad Sci U S A 2016, 113, E6919. 2a) , , , Science 1999, 284, 1318; b) , , Lancet 2001, 358, 135. 3a) , , , , , Nat. Rev. Microbiol. 2017, 15, 740; b) , , , , , , , , , , , , , Adv. Mater.

Nov 9, 2024 | onlinelibrary.wiley.com | Wei Zhang |Yang Lv |Qiang Niu |Can Zhu

Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description smll202406356-sup-0001-SuppMat.docx14.3 MB Supporting Information References 1, , , , , , , , , , , , , ACS Nano 2023, 17, 15568. 2, , , , , , , , , , Adv. Healthcare Mater. 2024, 13, 2303548. 3, , , , , , , , , , Nat. Commun. 2024, 15, 233. 4, , , , , , , , , ACS Appl. Mater. Interfaces 2018, 10, 193. 5, , , , , , , , , , , Nano Today 2022, 42, 101368.

Jan 19, 2024 | onlinelibrary.wiley.com | Minchao Liu |Yiyang Wang |Chenxing Lu |Can Zhu

Conflict of interest The authors declare no competing financial interest. Supporting Information As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.

Nov 27, 2023 | thieme-connect.com | Tianyu Zhang |Can Zhu

Buy Article Permissions and Reprints All articles of this category Enzymatic kinetic resolution (EKR) of racemates has been considered as an efficient and scalable technology to deliver enantiopure substances in an environmentally benign way. Herein, we develop a practical EKR of α-allenols enabled by a commercially available immobilized lipase, Lipozyme TL-IM. The stereoselectivity factor (S-factor) of this kinetic resolution (KR) was investigated to reach up to >1000.